Prosecution Insights
Last updated: April 19, 2026
Application No. 18/763,683

SYSTEMS AND METHODS FOR DETECTING CHANNEL MEMBERSHIPS MENTIONS USING ARTIFICIAL INTELLIGENCE

Final Rejection §103
Filed
Jul 03, 2024
Examiner
LE, RONG
Art Unit
2421
Tech Center
2400 — Computer Networks
Assignee
Google LLC
OA Round
2 (Final)
68%
Grant Probability
Favorable
3-4
OA Rounds
3y 4m
To Grant
98%
With Interview

Examiner Intelligence

Grants 68% — above average
68%
Career Allow Rate
295 granted / 435 resolved
+9.8% vs TC avg
Strong +30% interview lift
Without
With
+29.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 4m
Avg Prosecution
34 currently pending
Career history
469
Total Applications
across all art units

Statute-Specific Performance

§101
5.3%
-34.7% vs TC avg
§103
58.2%
+18.2% vs TC avg
§102
13.8%
-26.2% vs TC avg
§112
11.1%
-28.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 435 resolved cases

Office Action

§103
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Miscellaneous Claims pending: 1-20 Claims amended: 1, 3, 9, 11, 17, Claims cancelled: 2, 10, 18, New claims: n/a Response to Arguments Applicant’s arguments, with respect to the rejection(s) of claim(s) 1, 9, 17, have been fully considered. Regarding applicant’s remarks dated 12/01/2025, regarding none of the currently cited reference teach the amended portions of claims 1, 9, 17. However, upon further consideration, a new ground(s) of rejection is made in view of Ben-Itzhak in combination with Adimatyam, see below action for detailed explanation. Applicant’s arguments, with respect to the rejection(s) of dependent claim(s) 3-8, 11-16, 19-20, have been fully considered, they are rejected based on the same reasons as independent claims 1, 9, 17, above. Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 1, 3-5, 7, 9, 11-13, 15, 17, 19-20, is/are rejected under 35 U.S.C. 103 as being unpatentable over (US 20170250930) to (Ben-Itzhak) in view of (US 20100262986) to (Adimatyam) Regarding claim(s) 1, 9, 17, Ben-Itzhak teach identifying, by a processing device of a content sharing platform, a media item associated with a channel of the content sharing platform; obtaining data related to the media item; providing, as input to an artificial intelligence (AI) model, a prompt to cause the AI model to identify, from the data related to the media item, one or more mentions of channel memberships associated with the channel; receiving an output from the artificial intelligence (AI) model; and performing an action based on the output. (P. 16, 20-21, 38, 42, 67, 70, engage in an interaction such as dialog between the user and the conversation agent is executed using an AI engine to enable an automated conversation. The personalized content recommendation system (“Chatbot system”) receives the one or more messages (e.g., text, voice, video, gesture, etc.) from the user in an active conservation or user session and generates one or more personalized content recommendations, conversation agent provides prompts and/or dialogue to engage the user and collect user signals, a conversation agent 120 is operatively coupled to an AI engine 122 configured to receive messages from the user device 10, analyze the received messages, and transmit a contextually appropriate response to the user device 10, the user interactive communication platform (e.g., a messaging application, an Internet of Things device, a Virtual Reality device, an Augmented Reality device, a webpage, a website etc.), provide interactions with users on behalf of a particular publisher (e.g., CNN, ESPN, etc.), which reads on (memberships associated with channel)). Ben-Itzhak further teach a system comprising: a memory; and a processing device, coupled to the memory, the processing device to perform operations, and A non-transitory computer-readable medium comprising instructions that, responsive to execution by a processing device, cause the processing device to perform operations. (P. 34, 45, 111-116, 121) Ben-Itzhak further teach wherein the action comprises: generating a recommendation reflecting enabling channel memberships on the channel; … wherein a channel membership provides users of the content sharing platform with one or more particular tiers of content access to the channel. (P. 38, 60, 90, multiple conversation agents 120 may be maintained by the Chatbot system 100. The individual conversation agents 120 may be configured to provide interactions with users on behalf of a particular publisher (e.g., CNN, ESPN, etc.) a user may elect to subscribe to a CNN Chatbot, wherein the user engages in interactions (e.g., conversations) with a conversation agent configured to converse and provide recommendations relating to the information and content served by the CNN publisher, in addition, Chatbot system 100 may provide a content recommendation which includes an invitation, suggestion, of link to subscribe to a publisher-specific or topic-specific Chatbot, depending on the interests identified of the user, Chatbots and their associated conversation agents may be “nested” as part of a recommendation provided by the Chatbot system, which reads on (a channel membership provides users of the content sharing platform with one or more particular tiers of content access to the channel), For example, the user may subscribe to an ESPN Chatbot which filters or scopes the conversations to sports related content. In this regard, the user may add to his or her contact list multiple contacts relating respectively to many different publishers, companies, services, websites, applications, and systems to enable engagement in conversations that are scoped to a particular genre, topic, category, knowledge area, product etc.). Ben-Itzhak teach the recommendation. Ben-Itzhak fail to specifically teach providing, for a channel owner of channel, an indicator referencing content. Adimatyam teach providing, for a channel owner of channel, an indicator referencing content. (Fig 1, 6, P. 8-10, 12, 14, 16, 57-59, collectively record the viewing history of viewers and update their profiles, report back to the content provider 140 from media center computing device 120, for better accurately target viewer interested content in future content selection) Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Ben-Itzhak by providing, for a channel owner of channel, an indicator referencing content as taught by Adimatyam in order to deliver many different types of content in an easy manner. Regrading claim(s) 3, 11, Ben-Itzhak in view of Adimatyam teach the method, the system, and the non-transitory computer-readable medium, the data related to the media item, the output. Ben-Itzhak further teach providing, for a channel owner of the channel, an indicator referencing the recommendation. (P. 16, 20-21, 38, 42, 67, 70, engage in an interaction such as dialog between the user and the conversation agent is executed using an AI engine to enable an automated conversation Via one or more messages (e.g., text, voice, video, gesture, etc.) from the user in an active conservation or user session and generates one or more personalized content recommendations). Regrading claim(s) 4, 12, 19, Ben-Itzhak in view of Adimatyam teach the method, the system, and the non-transitory computer-readable medium, the action, the media item, the channel memberships. Ben-Itzhak further teach embedding, in media item, a trigger to emphasis, during one or more portions of the media item, a button associated with channel memberships. (Fig. 7, 8, P. 24, 77, user action trigger choices or options include: keyword or input action buttons). Regrading claim(s) 5, 13, 20, Ben-Itzhak in view of Adimatyam the method, the system, and the non-transitory computer-readable medium, the output, the media item, the channel memberships. Ben-Itzhak further teach output classifies each identified mention into one or more categories. (P. 58, 75-77, 80 content recommendation scope used to organize and/or constrain the content recommendation entities based on one or more content characteristics (e.g., a source of the content, a category associated with the content,)). Regrading claim(s) 7, 15, Ben-Itzhak in view of Adimatyam teach the method, the system, and the non-transitory computer-readable medium. Ben-Itzhak further teach prompt includes a type of format to structure the output. (P. 67, 69, prompts relating to preferred reading topics for the user (e.g., news, technology, sports, finance, trending topics, entertainment, etc.), preferred sources of information (e.g., leading publishers or websites, news channels, etc.), a location of the user device, a preferred language, etc. In an implementation, the conversation agent may provide the user with a list of conversational commands configured to guide the user through various optimal or exemplary interactions with the conversation agent). Claim(s) 6, 14, is/are rejected under 35 U.S.C. 103 as being unpatentable over (US 20170250930) to (Ben-Itzhak) in view of (US 20100262986) to (Adimatyam) in view of (US 12363397) to (Yanamandra) Regarding claim(s) 6, 14, Ben-Itzhak in view of Adimatyam teach the method, the system, and the non-transitory computer-readable medium, the data related to the media item, the output. Yanamandra further teach output includes a timestamp of each identified mention. (C. 13, L. 42-50, the question 150 includes (or is associated with) a timestamp 152 that indicates a portion of the video that has been output (e.g., displayed as video and/or output as audio) by the viewer device 130 when the question was generated during the playing.). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Ben-Itzhak in view of Adimatyam by output includes a timestamp of each identified mention as taught by Yanamandra in order to effectively performing a machine learning (ML) cinematic (e.g., movie) question answering. Claim(s) 8, 16, is/are rejected under 35 U.S.C. 103 as being unpatentable over (US 20170250930) to (Ben-Itzhak) in view of (US 20100262986) to (Adimatyam) in view of (US 20250133275) to (Sahasi) Regarding claim(s) 8, 16, Ben-Itzhak in view of Adimatyam teach the method, the system, and the non-transitory computer-readable medium, the data related to the media item. Sahasi further teach an audio transcription of media item. (P. 124, automated speech recognition engine may process audio data and output a transcription(s) of the audio portions of the media content provided). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Ben-Itzhak in view of Adimatyam by an audio transcription of media item as taught by Sahasi in order to efficiently or adequately determine the most important portions of the content provided, such as those that may highly interest a viewer(s). Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to RONG LE whose telephone number is (571)270-7637. The examiner can normally be reached M-F (9 am - 6pm). Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nathan Flynn can be reached at 5712721915. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /RONG LE/Primary Examiner, Art Unit 2421
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Prosecution Timeline

Jul 03, 2024
Application Filed
Sep 04, 2025
Non-Final Rejection — §103
Nov 24, 2025
Examiner Interview Summary
Nov 24, 2025
Applicant Interview (Telephonic)
Dec 01, 2025
Response Filed
Jan 09, 2026
Final Rejection — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
68%
Grant Probability
98%
With Interview (+29.7%)
3y 4m
Median Time to Grant
Moderate
PTA Risk
Based on 435 resolved cases by this examiner. Grant probability derived from career allow rate.

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